Technical systems can be described using discrete states and state-changing events. Stochastic discrete-event systems (SDES) capture the systems’ behavior randomness and the probabilities of decisions. Zimmermann presents a novel and unifying framework for modeling and evaluating SDES.

The book is aimed at researchers and graduate-level students. Familiarity with basic concepts of linear algebra, probability, stochastic processes, and state space models is required; most first-year graduate students in the systems and control area have this background.

The introduction touches on engineering problems that may be tackled by the theory presented. The book is divided into three parts devoted to the modeling, evaluation, and applications of SDES. Part 1 has five chapters. Chapter 2 gives a unified description of SDES by defining an abstract model class for SDES. This unified description is used as an interface between model description and model evaluation. Chapters 3 to 6 are devoted to stochastic time automata, queueing models, and colored Petri nets.

The second part is divided into six chapters devoted to various problems related to the estimation of parameters of the model, optimization, and simulation. Chapter 7 gives standard quantitative evaluation methods for SDES with estimation of steady-state measures and transient measures. Approximation methods are the subject of chapter 8. Chapter 9 presents the efficient simulation approach to the analysis of SDES models. Chapter 10 describes methods of optimization for the models. Both simulation-based and nonsimulation-based methodologies are explored. The model-based direct control of SDES can be found in chapter 11, with a control interpretation for Petri nets. Chapter 12 is devoted to the description of software support tools. Modeling and evaluation of nontrivial technical systems can only be applied with the support of appropriate software tools. The main software tool for modeling and performing ability evaluation is TimeNET 4.0. Its functionality is continuously enhanced by including the research results of the modeling and performance evaluation group of Technische Universität (TU) Berlin. It is based on the DSPNexpress software package, which was developed at TU Berlin.

The third part contains applications of the unified modeling approach. The examples refer to optimization of manufacturing systems, analysis of communication systems, supply chain design and performance evaluation, and design and control of production cells.

Finally, the book examines standard and recently developed algorithms for the performance evaluation, optimization, and control of SDES in the context of the abstract model class. The extensive reference list is an excellent starting point for further reading and research.